The integration of camera systems into devices has created a large variety of systems of different shapes and sizes. These devices include smart phones, surveillance cameras, wearable cameras, camcorders, digital single-lens reflex cameras, mirror-less cameras, and tablets, as examples.
These camera systems can produce tradeoffs in image quality, device size, and costs. However, the desire for improved image quality remains the same as the systems and capture platforms may change. For example, digital images and video frames can have issues with image quality based on sharpness, noise, distortions, artifacts, and chromatic aberration.
In image processing and photography, aliasing is an effect that causes different signals to become indistinguishable or aliases of one another when sampled. Any digital image sampling system may suffer from aliasing when the input signal's frequency is higher than the Nyquist frequency of the system. For digital images, distortions and artifacts can result when the image reconstructed from samples is different from the original scene. For digital color images reconstructed by color image sampling systems, colors different from those in the actual scenes may appear in some regions of reconstructed color images due to aliasing. Such false colors are more noticeable and generally call “color aliasing”.
Most existing modern color imagine sensors have a color filter array (CFA), which is a mosaic of tiny color filters placed over each pixel. The most famous CFA pattern is the Bayer pattern. Imaging sensors equipped with a CFA tend to suffer from color aliasing from processing. In order to suppress color aliasing, filters such as optical anti-aliasing filters are generally applied in front of a color-imaging sensor. However, these filters result in a tradeoff in picture quality as the filters reduce the overall sharpness of a captured image.
Thus, a need still remains for an image processing system that can deliver sharpness in picture quality while still removing and suppressing the disadvantages of color aliasing. In view of the increasing demand for providing higher resolution images and videos, it is increasingly critical that answers be found to these problems.
Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems. Solutions to these problems have been long sought but prior developments have not taught or suggested any solutions and, thus, solutions to these problems have long eluded those skilled in the art.